Outcomes of the equivalence of adaptive ridge with least absolute shrinkage

Advances in Neural Information Processing Systems

Volumn , Issue , 1999, Pages 445-451

  Grandvalet, Yves ^a   Canu, Stéphane ^a  

^a UNIVERSITÉ DE TECHNOLOGIE DE COMPIÈGNE   (France)

Author keywords

[No Author keywords available]

Indexed keywords

REGRESSION ANALYSIS;

ADDITIVE MODELS; FIXED-POINT ALGORITHMS; HYPER-PARAMETER; KERNEL SMOOTHING; LEAST ABSOLUTE SHRINKAGE AND SELECTION OPERATORS; MODEL COMPLEXITY; RIDGE REGRESSION; SPARSE REGRESSION;

SHRINKAGE;

EID: 0041879258     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. L. Breiman. Heuristics of instability and stabilization in model selection. The Annals of Statistics, 24(6):2350-2383, 1996.
2. D.L Donoho and I.M. Johnstone. Minimax estimation via wavelet shrinkage. Ann. Statist., 26(3): 879-921, 1998.
3. F. Girosi. An equivalence between sparse approximation and support vector machines. Technical Report 1606, M.I.T. AI Laboratory, Cambridge, MA., 1997.
4. Y. Grandvalet. Least absolute shrinkage is equivalent to quadratic penalization. In L. Niklasson, M. Boden, and T. Ziemske, editors, ICANN'98, Volume 1 of Perspectives in Neural Computing, pages 201-206. Springer, 1998.
5. W. Hardie. Applied Nonparametric Regression, Volume 19 of Economic Society Monographs. Cambridge University Press, New York, 1990.
6. T.J. Hastie and R.J. Tibshirani. Generalized Additive Models, Volume 43 of Monographs on Statistics and Applied Probability. Chapman & Hall, New York, 1990.
7. D. J.C. MacKay. A practical Bayesian framework for backprop networks. Neural Computation, 4(3):448-472, 1992.
8. R. M. Neal. Bayesian Learning for Neural Networks. Lecture Notes in Statistics. Springer, New York, 1996.
9. S.J. Nowlan and G.E. Hinton. Simplifying neural networks by soft weight-sharing. Neural Computation, 4(4):473-493, 1992.
10. R.J. Tibshirani. Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society, B, 58(1):267-288, 1995.